Title :
Based on Improved BP Neural Network to Forecast Demand for Spare Parts
Author :
Ren, Jiafu ; Xiao, Min ; Zhou, Zongfang ; Zhang, Fang
Author_Institution :
Sch. of Manage. & Econ., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
According to the historical data of the x x factory the BP artificial neural network model is used, and a mapping relationship between the input and the output value of spare parts demand is set up. Model training results show that the model can better predict, with high accuracy. On this basis, this article forecasts the spare parts demand of the enterprise on 2008.
Keywords :
backpropagation; demand forecasting; maintenance engineering; neural nets; production facilities; backpropagation; demand forecasting; enterprise; factory; improved BP artificial neural network; mapping relationship; model training; spare parts demand; Artificial neural networks; Conference management; Demand forecasting; Economic forecasting; Mathematical model; Neural networks; Neurons; Predictive models; Production facilities; Technology forecasting; Artificial neural network; BP network; Demand forecasting; Spare parts;
Conference_Titel :
INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5209-5
Electronic_ISBN :
978-0-7695-3769-6
DOI :
10.1109/NCM.2009.31
